- Access after July 1, 2024: YES, through September 30, 2024
- Access to IU's research computing will remain unchanged for 90 days, but you will lose access to IU's research resources and data after September 30, 2024.
- The Rosen Center for Advanced Computing (RCAC) operates all centrally maintained research computing resources. RCAC provides advanced computational resources and services to support Purdue faculty and staff researchers. RCAC also leads research and partners with researchers to enhance the capabilities of resources. Services offered by RCAC include:
Community Clusters: World-class computational clusters at a fraction of the cost of workstations and servers, managed and supported centrally.
Research Storage: Variety of research storage to meet research storage needs, runtime storage, cold storage (cold backup), regulated compute environments, AI, and more.
Research Data Network: High-speed network infrastructure designed to facilitate transfer of large quantities of data produced by and analyzed on Purdue’s high-performance computing systems.
Partner on Research Proposals: Support and advance research discovery at Purdue through partnerships with faculty and research groups.
Computational, AI, and Data Science Skills: Domain-specific and general computational skills including software and workflow development provided by skilled research and computational scientists.
Training: Frequent workshops and training videos on various research computing, data, and AI topics.
Outreach: Participation in events and engagement with research computing enthusiasts
ACCESS: Support for NSF-funded Advanced Cyberinfrastructure Coordination Ecosystem Services and Support (ACCESS) through computing and data resources (Anvil) and staff expertise
REED+: Research ecosystem including storage and high-speed computing capability to handle Purdue’s control led research data and processing needs in a manner compliant with the highest level of cybersecurity applicable.
Center for Research Software Engineering: Accelerate research through software engineering support
Envision Center: Assist, support, and collaborate with faculty, students, and industry in scientific visualization, virtual and augmented reality and media creation.
- List RCAC Solutions include:
◊ Compute:
Negishi, Bell: HPC community clusters for majority of computing tasks, including single-thread well as multi- and many-core parallelism
Gautschi: HPC and AI community cluster that will be deployed in 2024 and will include dense CPU nodes as well as GPUs
Gilbreth: HPC Community cluster for GPU-enabled research
Geddes: Private Cloud
Weber: HPC cluster for research under export control
Scholar: Compute cluster for classroom learning
Hammer: community cluster optimized for loosely coupled high-throughput computing
Anvil: HPC cluster and private cloud for national NSF ACCESS and NAIRR
Open OnDemand: A web-browser-enabled interface to computing resources on HPC clusters.
Thinlinc: An alternative to running an X11 server directly on compute that allows graphical interactive jobs run directly on compute cluster
Applications: Thousands of applications and containers, including bioinformatics application, are supported on HPC clusters. A software catalogue is available via user guides.
◊ Storage:
Data Depot: High-capacity, fast, reliable and secure research data storage for majority of research data storage needs (POSIX file system)
Scratch Storage: Parallel file system on each community cluster optimized for runtime compute and data-intensive needs
Home Directories: Personal research data storage for HPC needs
Fortress: Large, long-term, multi-tiered file caching and storage system
Depot Object: Object storage that facilitates access through S3-compatible APIs.
Not sure what you need? please visit Storage Solution Finder.
◊ Data migration: Globus provides a powerful and easy-to-use file transfer service. Globus is RCAC’s recommended service for transfer of research data to storage solutions managed by RCAC. It provides an easy-to-use interface and a reliable mechanism to transfer or share data.
◊ Need further support? Please visit user guides and RCAC website for additional information. For further support, please contact rcac-help@purdue.edu